KDM3B inhibitors disrupt the oncogenic activity of PAX3-FOXO1 in fusion-positive rhabdomyosarcoma

Fusion-positive rhabdomyosarcoma (FP-RMS) is an aggressive pediatric sarcoma driven primarily by the PAX3-FOXO1 fusion oncogene, for which therapies targeting PAX3-FOXO1 are lacking. Here, we screen 62,643 compounds using an engineered cell line that monitors PAX3-FOXO1 transcriptional activity identifying a hitherto uncharacterized compound, P3FI-63. RNA-seq, ATAC-seq, and docking analyses implicate histone lysine demethylases (KDMs) as its targets. Enzymatic assays confirm the inhibition of multiple KDMs with the highest selectivity for KDM3B. Structural similarity search of P3FI-63 identifies P3FI-90 with improved solubility and potency. Biophysical binding of P3FI-90 to KDM3B is demonstrated using NMR and SPR. P3FI-90 suppresses the growth of FP-RMS in vitro and in vivo through downregulating PAX3-FOXO1 activity, and combined knockdown of KDM3B and KDM1A phenocopies P3FI-90 effects. Thus, we report KDM inhibitors P3FI-63 and P3FI-90 with the highest specificity for KDM3B. Their potent suppression of PAX3-FOXO1 activity indicates a possible therapeutic approach for FP-RMS and other transcriptionally addicted cancers.

and not the original Kruidenier et al publication?IC50 should be used in connection with inhibitory assays, EC50 in connection with cell-based assays-the authors do not always use it in this way.I would suggest avoiding "drug-like" properties (line 190).Is any metal included in the NMR binding experiments?How do the authors explain higher binding constants (SPR) compared to more potent inhibition, both in cells and against purified protein?It would be good to highlight which constructs have been used for which biochemical assay-it appears to be different (full-length vs truncated KDM).* Cellular mechanism of action studies: the GSEA analyses support a combined effect of KDM1A and KDM3b (whilst the biochemical analysis for KDM1A appears weak at this point, see above).Is it possible that other components of a KDM1 complex are regulated by KDM3b?Analysis of chromatin states and CHIP-seq data provides useful pieces to the puzzle by highlighting H3K9 methylation as a key factor, in line with the biochemical activity of KDM3b, whereas the contribution of KDM1A to H3K4 levels is less clear.Figure 5 is important to the conclusions, in particular, 5A and B should be enlarged to increase readability and interpretation.Several of the programs used for analysis are not referenced.Are there any KDM1A and KDM3B CHIP-seq data available to look deeper into direct target genes and chromatin locations?It appears that H3K9me changes are significant contributors to the observed phenotypic effects-how is this accomplished?Although H3K9methylation plays a key role in heterochromation formation, is that really the case in the scenario described?Are there HP1 Chip-seq data available for their system?If heterochromatin formation and silencing of key loci is not the mechanism in their system, what could lead to transcriptional regulation (ie which other chromatin factors with H3K9 binding domains could mediate the observed effects)?Figure 7 with the presumed MoA appears highly hypothetical at this point.Minor comments related to this section: how was dosage determined in the in vivo experiments?Are there any exposure studies/data for PFI90?In an ideal case studies on primary tumour material would be preferred (in my view) over animal model systems and cell line experiments in order to conclude on clinical/therapeutic utility.* METHOD section: in general, several of the various Materials and Methods chapters (p 29 ff, submitted manuscript) require serious copy editing in order to improve readability and reproducibility.Much of the biochemical protein work (include structural analysis, docking, KDM assay) is insufficiently or not at all described.Much of the biochemical and medchem KDM foundation was laid by the Structural Genomic Consortium and its academic and private partners (for example construct design, cloning, biochemical and structural characterisation, tool compounds; resources that have been shared with Addgene but also Eurofins) and has not been adequately recognized in this manuscript-for example I would expect mention of the PDB codes used for structural modelling, or mention of the PIs in the cloning and construct design (as stipulated by Addgene on their website how to use/cite the resources).The in vitro assay conditions (largely outsourced to Eurofins) need to be stated.Similarly, the peptide substrate sequence for their in vitro KDM assays needs to be detailed (I could not immediately find it in their submitted manuscript).I could not find in the M&M section how they produce/express affinity tagged constructs for their SPR experiments.There is no mention how the authors performed the docking experiments of their identified compounds.analysis and enzymatic assays, they showed that PFI-63 targets histone lysine demethylases (KDMs) with highest selectivity for KDM3B.They conducted structural similarity search to improve the solubility and potency of PFI-63 with a new compound PFI-90.They then analyzed PFI-90 binding to KDM3B using NMR and SPR.Additional in vitro and in vivo studies further confirmed the effectiveness of PFI-90 in suppressing growth of FP-RMS.Overall, this is a well designed study that identified a potential new drug candidate for treating FP-RMS and a set of in vitro and in vivo analyses aim to characterize the mechanisms of how PFI-90 works.
The authors may want to consider the following points to improve the manuscript.In particular, as it is important to investigate how inhibition of the general enzymes of KDMs impacts cell growth, the analyses of the histone ChIP-seq and Hi-C data need to be enhanced.
1. KDMs including KDM3B are broadly expressed in many cell types.Supplementary Fig. 2 and 4 showed PFI-63 and PFI-90 inhibition of cell growth in almost all 60 cancer cell lines.Can they also test some normal cell lines and discuss possible side effects?Any symptoms observed in the mice in the in vivo experiments?2. Fig. 5B shows PFI-90 increases H3K4me3 and H3K9me2.Does PFI-90 increase H3K4me3 and H3K9me3 for all genes or specifically for PAX3-FOXO1 target genes?Fig. 5A shows almost no change of ChromHMM states in PAX3-FOXO1 sites.In other words, would inhibition of KDM3B by PFI-90 suppress cell growth by reducing transcription in general?They compared PFI-90 vs. DMSO on PAX3-FOXO1 binding sites.If they compare PAX3-FOXO1 binding sites vs. non-binding sites in PFI-90 treated cells, is there any difference between histone modifications? 3. A technical question on Fig. 5A, why there is almost no signal for H3K9me2 in DMSO even in the heterochromatin state? 4. Fig. 5C shows that the top 10% of enhancers with the most H3K9me2 increase overlaps significantly with PAX3-FOXO1 sites.It'd be helpful to report the total binding sites of all the TFs listed in the figure.Two scenarios should be distinguished: one is that the H3K9me2 specifically increases in PAX3-FOXO1 sites and another is PAX3-FOXO1 has many more binding sites than the other TFs and it is thus natural to have more overlap with the affected enhancers.5.While H3K27ac intensity does not increase in PAX3-FOXO1 sites, does its intensity increase in all the enhancers?Also, what is the number of H3K27ac peaks in PFI-90 treated cells compared to DMSO? 6.As the histone modifications interplay with each other, KDM3B inhibition may have broad impact on histone modifications.For the ChIP-seq of histone marks, it'd be helpful to identify differentially modified regions between PFI-90 and DMSO.Then check whether the PAX3-FOXO1 sites and target genes are associated with these differentially modified regions.
7. The authors conducted Hi-C experiments to investigate whether chromatin structure is affected by PFI-90 treatment, which is important for understanding how PFI-90 inhibition of KDMs suppresses cell growth.Some additional quantification is needed for the analysis.
First, the similarity of the Hi-C maps between PFI-90 and DMSO should be quantified using such as HiCRep.This will provide a refence to call difference between the two Hi-C experiments.
Second, there are many methods to detect the differences between Hi-C contact maps such as CHESS (Galan, Nat. Genet., 2020), Zebra (Vian, Cell, 2018), which will give more systematic assessment of the chromatin structure difference.
Third, the chromatin structure difference may become easier to detect while guided by the differentially modified histone marks.Loop, TAD and compartment comparison can be focused on the regions with differentially modified H3K27ac, H3K9me2, H3K9me3 and H3K4me3.
Fourth, histone modification changes may alter the modularity of the chromatin structure as shown in a recent study (Zheng and Wang, Nat Commons, 2022).It'd be interesting to compare chromatin modularity changes between PFI-90 and DMSO and check how it affects PAX3-FOXO1 target genes and binding sites.
Reviewer #3: Remarks to the Author: In their manuscript titled "KDM3B inhibitors disrupt PAX3-FOXO1 oncogenic activity in fusion positive rhabdomyosarcoma," Kim et al. describe a high throughput screen (HTS) using an ARMS cell line engineered to report PAX3-FOXO1 transcriptional activity.As a control, they use a CMV driven reporter line.They identified 64 hits that had specific activity in dose response (DR) and performed in-depth analysis of PFI-63.The molecule altered myogenic differentiation program expression and apoptosis.Timecourse studies were carried out.Another molecule (PFI-90) was identified that had better physical/chemical properties.Within the error for such assays (typically 5-10 fold) these two compounds were equivalent in terms of cellular EC50.The authors went on to show that the molecules inhibited KDM family members with highest potency for KDM3B.However, the IC50 for the enzymes including KDM3B was similar or higher than that for the cells.Binding was analyzed by NMR and SPR and all assays showed similar binding constants (5-10 uM).They went on to perform epigenetic and chromatin profiling and perform dependency screening for KDM3B.They noted that KDM3B was not a dependency in the PedDep portal.They performed limited in vivo testing.Overall, the team set out to identify a PAX3-FOXO1 transcriptional inhibitor and found a small molecule that has modest activity on cells (low micromolar) that they argue inhibits KDM3B.The major concern is the poor binding constant for KDM3B protein and ruling out non-specific effects of the drug on cellular state and survival.

Concerns:
1) The EC50 is between 1-10 uM for both compounds and the curve is very steep which raises concerns about specificity of targeting.The authors performed a comprehensive series of studies to try to demonstrate specificity such as NMR and target gene knockdown.
2) The enzyme inhibition assays for the KDM family members are in vitro assays and show weak inhibitor activity.This is a major concern.How can the cellular EC50 be similar or lower than the enzyme IC50 activity?I suspect the authors will argue that it inhibits multiple family members and this explains the difference.The concern is that this is a non-specific effect on the cells and that would be consistent with the lack of ARMS selectivity.To address this concern, the authors can: a. Demonstrate direct binding of the protein inside cells.b.Compare their compound to other KDM inhibitors mentioned in the discussion.c.Obtain a crystal structure of the compound bound to protein pocket.d.Make an inactive isomer to distinguish between non-specific chemical properties and selective targeting.e. Test other epigenetic drugs in their reporter assay.How do their inhibitors compare to the clinically relevant epigenetic drugs?
3) The drug does not appear to be selective for ARMS.A head to head comparison between ARMS and ERMS using O-PDXs may be beneficial.
Reviewer #4: Remarks to the Author: In this manuscript, Kim et al. attempt to identify novel therapeutic targets for fusion-positive alveolar rhabdomyosarcoma (FP-RMS).Using a small molecule screening approach, they identify one candidate compound as a therapeutic inhibitor of the tumorigenic PAX3-FOXO1 fusion transcript.They then characterize the downstream mechanisms of this compound using multiple complementary approaches, including functional genomics and molecular dynamics simulations, which indicate proteins from the KDM family as putative targets.Finally, they identify a more powerful analog molecule and demonstrate its pre-clinical potential using in vivo xenograft models.The authors generate a wealth of functional genomics data to characterize their candidate compounds, including bulk and single-cell RNA-seq, ChIP-seq, Hi-C, and ATAC-seq data.While the presented results generally align and support the authors' claims, the lack of extensive QC and methodology precludes critical evaluation of some of the results presented here -mainly regarding the functional genomics characterization of the compounds.Therefore, the manuscript will significantly benefit from a comprehensive revision of the methods section and the inclusion of detailed QC for the functional genomics data.
# Major comments * There is a noticeable absence of QC and methodology for all the functional genomics data.The authors should extensively revise their method sections for the functional genomics analyses and provide supplementary figures with QC metrics for each assay.The lack of this information precludes any rigorous evaluation of the methodology used and, consequently, the results presented by the authors.For instance, it is unclear how many libraries were generated for each modality, given that there is no supplementary table detailing the datasets from this study (assay, treatment, time points, sequencing depth, number of cells if applicable, etc.).For example, were the RNA-seq libraries generated in triplicate, quadruplicate, n=1?Were technical or biological replicates used?This critical information is missing.Other examples of lacking methods include a description of the EDEN, ChEA, and Enricher analyses (and corresponding references).Similarly, other details are missing.How were Drosophila spike-ins added to the sample(s), and how were these reads used to normalize the ChIPseq data?The same is true for the ATAC-seq data.How were the pre-ranked log2 fold changes calculated for the ChIP-seq data?How were peak calls performed in the ATAC-seq data?And how were they linked to genes for the GSEA analyses?What genes comprise the gene set induced by treatment with the KDM1A /LSD1 inhibitor SP2509, and where were they obtained?If non-default parameters were used for any software, then the text should describe them or make it explicit that default parameters were used.QC plots should include, for example.MA or volcano plots for RNA-seq data, TSS enrichment plot(s) for ATAC-seq (from ataqv, for example).
* I suspect the scRNA-seq clustering captured substantial technical heterogeneity.However, unless the technical sources of variation are extensively characterized and mitigated, it becomes difficult to evaluate the underlying biology described here accurately.For example, solely based on the data presented by the authors, it is not possible to confidently say that the differences in cell number between DMSO and PFI-90-treated cells in cluster 2 are not driven by unaccounted technical variation between the two samples during integration.The threshold of median ±3 SD for % mitochondrial reads can be very permissive depending on how the data behaves, leading to low-quality barcodes being included.What were the actual cutoffs used for each sample?Assessing this information without additional QC plots and detailed methods is impossible.Based on the methods section, it is unclear if the authors performed clustering before or after removing doublets.Did the authors account for %MT reads and other technical factors as covariates for the SCT normalization?The authors should confirm they are correctly controlling for technical variation by quantifying, for example, the distribution of %MT and nUMI per scRNA-seq cluster.

REVIEWER COMMENTS
Reviewer #1, expertise in small molecule screening, scRNAseq, epigenetics, histone lysine demethylases (Remarks to the Author): Kim et al describe the identification of a compound series that is able to reduce transcriptional activity in a PAX3-FOXO1 reporter cell line, ultimately leading to apoptosis and myogenic differentiation.The PAX3-FOXO1 fusion protein is a key oncogenic driver in fusion-positive alveolar rhabdomyosarcoma, an aggressive childhood malignancy.The authors provide evidence that the main mode of action of the identified compounds might lie in their ability to inhibit the enzymatic activity of histone lysine demethylases (KDMs), an important family of epigenetic modulators.The work describes the screening and target characterisation efforts and includes cellular and in vivo follow-up studies, aiming to support their target hypothesis of an anti-cancer effect of a broad-spectrum KDM inhibitor in rhabdomyosarcoma.As such, this manuscript provides an initial, important step to developing tools for oncology research, by highlighting a possible role of KDMs in fusionpositive rhabdomyosarcoma.

We thank the reviewer for the positive comments and the recognition of the importance of KDM function in PAX3-FOXO1 fusion gene driven rhabdomyosarcoma.
There are some compelling arguments in support of their hypothesis, however, at this point, I am hesitant to support the publication of the study in its current format.My criticism is related to the following areas: * Hit identification from compound screening, biochemical characterisation: the authors performed a compound library screening against a medium-sized collection of chemical matter; the initial hits were further reduced by providing scores and dose-response curves (not exactly described in detail how that was accomplished; cf line 109/110) resulting in the identification of compounds designated PFI63 and PFI90, the main objects of their work.
We apologize for the lack of detail regarding the drug screen.This was a 62,643 compound screen, the largest drug screen to date for rhabdomyosarcoma with consideration of 3 factors for determining PAX3-FOXO1 inhibition.The 3 factors are: 1. PAX3-FOXO1 binding site ALK enhancer driven luciferase as a direct readout for PAX3-FOXO1 transcriptional activity.2. CMV driven luciferase as a readout for general transcription.

XTT assay for cell viability.
The details of the screen have already been published and referenced (Gryder BE, et al 2019.Nat Commun 10, 3004).Given the limited space available, we chose to reference the details instead of describing it.However, we now include additional details in the text (page 4 lines 98-104) that we believe sufficiently describes the screen.
The authors employed Gene Set Enrichment Analysis (GSEA) and identified histone lysine demethylases as possible targets for their identified hits.Whilst this appears reasonable other mechanisms at work might be referred to -for example, other epigenetic manipulations (bromodomain inhibition, PRC2 manipulation such as JQ1, SUZ12) appear as significant hits in their transcriptional analysis, possibly highlighting complex epigenetic changes upon inhibition.At this point, an illustration of differentially regulated genes (heatmap) would be useful to highlight possible mechanisms and transcriptional targets.
We agree with the reviewer that complex epigenetic changes are likely happening.Since we cannot predict how inhibition of a specific enzyme will affect that enzyme's transcript level, it is difficult to directly look at differentially regulated genes to predict possible targets.
Rebuttal Figure 1.Leading Edge Gene analysis from GSEA software comparing PFI-90 vs DMSO at 24 hours.Analysis of gene set to gene set interaction by the fraction of shared leading edge genes.Group 1 are gene sets for PAX3-FOXO1 targets.Groups 2 and 3 have epigenetic gene sets including KDMs, PRC2, BRD4 and HDAC.
Hence, we performed additional analysis using leading edge analysis for P3FI-90(previously referred to as P3FI-90) using the GSEA desktop software focusing on gene sets with FDR < 0.05.This resulted in a gene set interaction map which showed 3 biologically related groups (Rebuttal Fig 1).The first group was the PAX3-FOXO1 gene sets which, as expected, shared multiple genes.The other groups included epigenetic gene sets for multiple KDMs, PRC2, and BRD gene sets, as you have indicated, which also share multiple genes.Thus, our previous and new analyses highlight these changes occurring across a wide range of important biological pathways that likely include both secondary and tertiary responses to KDM inhibition.Furthermore, many of the differentially expressed genes are regulated by multiple pathways and subsequently across multiple gene sets.Although intriguing, this complex interplay requires extensive experimentation to decipher, and we feel it is outside the scope of this manuscript.
A direct comparison of their putative KDM inhibitors described in this section (and Discussion) such as JIB-04, GSK-J4, GSK-690, and other KDM3 inhibitors) applied to their cell line system with bulk-RNAseq as readout would be useful to corroborate their argument.
Thank you for your suggestion.We performed bulk RNA-seq using JIB-04, GSK-J4, and GSK-690.We found that the multi-KDM inhibitors JIB-04 and GSK-J4 both downregulated PAX3-FOXO1 gene sets robustly.This result is consistent with our findings that KDM inhibition by P3FI-63 (formally known as PFI-63) and P3FI-90 disrupt PAX3-FOXO1 functions.The KDM1A inhibitor GSK-690 was not able to downregulate PAX3-FOXO1 robustly with only 1 downregulated gene set which was related to PAX3-FOXO1.However, GSK-690 was able to upregulate apoptosis gene set.These findings are consistent with our data from CRISPRi knockdown of KDM1A which showed downregulation of PAX3-FOXO1 albeit not as significantly as KDM3B and upregulated apoptosis gene sets.As for testing other KDM3 inhibitors JDI-4 and JDI-12, we were unable to find an easy way to purchase the compounds for testing.Additionally, as discussed in the text, the compounds JDI-4 and JDI-12 compounds were not tested on other KDMs and given the high homology between KDM family members, it is difficult to interpret the data since other KDMs may be inhibited by the JDI compounds.We included these new data in the manuscript as Supplementary Table S1 Tab4-6.Discussion of the results is on page 8 lines 169-174.We thank the reviewer for the suggestions to make our data more robust.
Similarity Ensemble Approach (SEA) analysis indeed suggests several 2-oxoglutarate dependent oxygenases (including several KDMs but also FTO) as possible molecular targets apart from several membrane protein mechanisms (which may constitute possible off-targets).At this point in the manuscript, it appears absolutely essential to expand significantly on the possible mode of inhibition using structural analyses.The corresponding Figure 1H allegedly displays the binding of the inhibitor in the active site of KDM3B (the figure needs to be displayed in a larger format).How is this pose determined (and ranked?) -there is no mention of the experimental/computational details except that Pymol is used to create the figure.Minimally the relationships/distances of the inhibitor with key active site residues, cofactor (2-oxoglutarate) as well as active site metal need to be displayed.Although KDM3B appears as one possible target KDM, modelling then should be performed against the other inferred KDMs as well.
We apologize for the confusion based on original Figure 1H. Figure 1H in the previous version is not a structure based on X-ray crystallography.We did attempt X-ray crystallography to determine the binding of P3FI-63/P3FI-90 to KDM3B.However, these experiments failed to produce crystals, on multiple occasions performed by experts at the NCI.To address the reviewer's concerns, we performed in silico structural docking experiments using ICM-Pro and PoketFinder from Molsoft (details in Methods section).P3FI-90 was tested against KDM3B, KDM4B, KDM5A, KDM5B, KDM6A, KDM6B.We found that P3FI-90 interacts with the metal ions in the active site of KDM3B, KDM4B, KDM5A, KDM5B, KDM6A, but not KDM6B (Fig 2E and Supplementary Figure 7).Hydrogen bond interactions at the active site showed that KDM3B has the most extensive hydrogen bond interaction and other KDMs had lower interaction which correlates with higher affinity for KDM3B.We also found that P3FI-90 docks well with a favorable score to the active site of LSD1.This is consistent with our inhibition assay which showed inhibition of both KDM3B and LSD1.Lastly, the docking experiment also showed that there may be an alternative binding site for KDM3B for P3FI-90 which indicates that P3FI-90 may have an allosteric inhibitor activity.The model in original Figure 1H has been removed and new structural analysis models have been added to Figure 2E and supplementary figure 7 as well as the Radial Convolutional Neural Net (RTCNN) scores as supplementary table S1, tab8.Discussion of these results are located on pages 9-12 lines 208-255.We thank the reviewer for suggestions to improve our manuscript.
Of critical consequence is also the alleged inhibition of KDM1A (LSD1), whose 3D structure importantly shows a completely different active site architecture compared to the Fe2+/2-oxoglutarate dependent KDMs such as KDM3B.How is inhibition achieved in light of those differences?
We agree with the reviewer that this is a critical point.It was a surprise to us when we found that P3FI-90 also inhibited LSD1 given that the 2-oxoglutatrate cofactor to Fe2+ interaction in the Jumonji family of KDMs are very different from the FAD-dependent action of LSD1.Interestingly, P3FI-90 has significant structural similarity with LSD1 inhibitor SP-2577 (Rebuttal Figure 2).
Additionally, as described above, in silico docking experiments show that P3FI-90 is predicted to dock inside the active site of LSD1 favorably (Figure 2E).Finally, we conclusively show by enzyme inhibition assay, clear inhibition of LSD1 by P3FI-90 (Figure 2C).We have included the fact that KDM1A inhibition was a surprise finding on page 9 lines 202-204.
Moreover, since a lot of the argument lies on proper biochemical characterisation of the KDMs with inhibitors detailed dose-response curves need to be included in their invitro work (only 2 inhibitor concentrations are shown as relative inhibition).What are the actual activities in their biochemical assays?Are these FDH/NADH assays or direct product determination assays using mass spectrometry?These details are not given in their experimental descriptions.
We apologize for this omission.As per the reviewer's suggestion, we now have included the details of the biochemical assay performed to determine the inhibition of enzymes in Figure 1G into the Supplementary Methods section.All of the KDM assays were Time Resolved FRET assays except for KDM1A.KDM1A is an antibody based detection of demethylated product using fluorescence.The Abcam kit (Cat ab113460) is described in the company website and is now included in the manuscript as supplementary methods.As for presenting the entire dose-response, Figure 1G and 2C have been replaced with a new figure incorporating the entire data.The highest concentration tested for each assay was 10 uM.
Moreover, based on the docking experiments, competition experiments could be designed to determine mode of action (cofactor or substrate inhibition, metal binding etc).
We apologize for the confusion regarding docking experiments as explained above.Original Figure 1H is not X-ray crystallography and therefore does not represent docking of P3FI-90 with KDM3B.We have performed numerous experiments attempting to create crystals with KDM3B and P3FI-63 or P3FI-90 but these have all failed.P3FI-63 was too insoluble and not amenable for crystals.P3FI-90 had better solubility but also did not form crystals.We were able to obtain crystals using NOG as the binding partner as was already published but when attempts were made to soak the crystal with P3FI-90 to replace NOG, the crystals fell apart.We have also attempted to obtain structural information using CryoEM, but only the structured enzymatic pocket was able to be visualized while the disordered portion of KDM3B was too difficult to stabilize for CryoEM.Hence, a competition experiment with resolution to determine docking was not feasible.As shown above, we did perform In Silico Docking experiments which shows that P3FI-90 is predicted to dock at the enzymatic pocket of KDM3B with interaction of the Mn metal.We have included the structural analysis models in Figure 2E and Supplementary Figure 7.
Minor comments related to this section: Do other HDACi than N1302 (used to refine MoA) show overlap with their profiles?
Yes, as you suspected, other HDAC inhibitors such as Sphingosine and Bisaprasin also showed the same pattern as N1302 where ALK-Luciferase was decreased while CMV-Luciferase was increased.They are part of the 64 compounds in Table 1 Tab1.
Is there a reason why a PhD thesis was cited for the KDM inhibitor GSK-J4 and not the original Kruidenier et al publication?
We are citing Hookway E to create a list of transcripts downregulated by GSK-J4.Unfortunately, the original Kruidenier et al 2012 Nature paper did not perform a genome wide transcriptome analysis.They performed a PCR based cDNA analysis focusing on the cytokine profile.In Hookway E's thesis, multiple myeloma and Ewing's sarcoma were treated with GSK-J4 and transcriptome analysis was performed using Microarrays.We added this gene set in the GSEA analysis and found it as a hit.We will be happy to remove this if the reviewer requires this.
IC50 should be used in connection with inhibitory assays, EC50 in connection with cell-based assays-the authors do not always use it in this way.I would suggest avoiding "drug-like" properties (line 190).
Thank you for pointing out the inconsistency.We have edited the text for consistency and appropriate usage of EC50 and IC50.

Is any metal included in the NMR binding experiments?
This is an astute question by the reviewer, and we apologize for this omission.For the NMR experiments, Iron was replaced with Zn.We attempted initial experiments with Iron but due to difficulty maintaining the proper ionization state, we switched to Zn.This approach for Iron based KDMs has already been reported (Leung IK, et al. 2013 Journal of Medicinal Chemistry 56 (2), 547).We have updated the Methods to include this information.
How do the authors explain higher binding constants (SPR) compared to more potent inhibition, both in cells and against purified protein?SPR Kd and cell free enzyme assay IC50 are in the single digit uM range.Cellular context is more complex and it is not uncommon to have a factor of difference from cell-free assays.Additionally, P3FI-63/P3FI-90 are multi-KMD inhibitors which may have biological effect at lower IC50.
It would be good to highlight which constructs have been used for which biochemical assay-it appears to be different (full-length vs truncated KDM).
Thank you for pointing this out.We have now edited the methods to point out the different KDM3B proteins used for each assay.* Cellular mechanism of action studies: the GSEA analyses support a combined effect of KDM1A and KDM3b (whilst the biochemical analysis for KDM1A appears weak at this point, see above).Is it possible that other components of a KDM1 complex are regulated by KDM3b?
It is true that many epigenetic factors are part of larger complexes with multiple partners including KDM1A.The hypothesis that KDM3B could be regulating the partner proteins of KDM1A complexes is intriguing.We know from cell free enzyme inhibition assay that KDM1A is directly inhibited by P3FI-90 and the in silico docking experiment showed that P3FI-90 binding to KDM1A had favorable binding score.Since KDM1A is directly inhibited by P3FI-90, teasing out possible indirect inhibition of KDM1A by KDM3B action would be challenging, and we feel is outside the scope of this manuscript.Thus, we feel that showing the strong evidence for inhibition of the primary targets of P3FI-63/P3FI-90 and their biological consequences to FP-RMS biology should be the main scope of this manuscript.
Analysis of chromatin states and CHIP-seq data provides useful pieces to the puzzle by highlighting H3K9 methylation as a key factor, in line with the biochemical activity of KDM3b, whereas the contribution of KDM1A to H3K4 levels is less clear.Figure 5 is important to the conclusions, in particular, 5A and B should be enlarged to increase readability and interpretation.
Thank you for your suggestion.We have now increased the size of both Figure 5A and 5B for easy reading.
Several of the programs used for analysis are not referenced.

We apologize for this omission and have now added references.
Are there any KDM1A and KDM3B CHIP-seq data available to look deeper into direct target genes and chromatin locations?It appears that H3K9me changes are significant contributors to the observed phenotypic effects-how is this accomplished?Although H3K9methylation plays a key role in heterochromation formation, is that really the case in the scenario described?Are there HP1 Chip-seq data available for their system?If heterochromatin formation and silencing of key loci is not the mechanism in their system, what could lead to transcriptional regulation (ie which other chromatin factors with H3K9 binding domains could mediate the observed effects)?
These are insightful questions.Since these experiments have not been done by us or others in fusion positive rhabdomyosarcoma, we performed ChIP-seq of KDM3B.We found that the binding of KDM3B correlated well with that of H3K9me2 using deepTools' plotCorrelation (Rebuttal Fig. 3).This was expected, given that H3K9me2 is the target of KDM3B.P3FI-90 treatment did not appreciably change KDM3B binding at TSS or PAX3-FOXO1 sites (See Below, Rebuttal Fig. 4) indicating that P3FI-90 likely inhibits KDM3B's enzymatic function and does not affect its recognition and binding of H3K9me2.We also performed ChIP-seq for HP1 and found that the pattern of binding of HP1 also correlated with H3K9me2 using plotCorrelation (Rebuttal Fig. 3).When looking at co-localization of HP1 and KDM3B, importantly, we found that there was a strong correlation in co-occupancy suggesting that KDM3B binding does indeed take place in heterochromatin.Interestingly, when looking at HP1, P3FI-90 treatment did increase HP1 binding at PAX3-FOXO1 sites.This may indicate that increase in H3K9me2 did increase heterochromatin like characteristics at PAX3-FOXO1 sites by increasing HP1.We have added this to the manuscript (Supplementary Figure 11D-F We also performed ChIP-seq of KDM1A which showed that its peaks qualitatively colocalized with those in H3K4me3 ChIP-seq experiment (Rebuttal Fig. 5).Due to the high background, peaks calls by MACS2 was limited as can be seen below.
Rebuttal Figure 5. ChIP-seq comparison of H3K4me3 with KDM1A using IGV viewer.Peak calling using MACS2 narrow peak calling set at p-value of 10^-7.
Figure 7 with the presumed MoA appears highly hypothetical at this point.
We have modified the discussion to indicate that the theoretical model requires additional studies to confirm the model.However, we believe that this theoretical model helps to create a framework for future discussion and hypothesis testing.This edit is located on page 30 lines 563-564.
Minor comments related to this section: how was dosage determined in the in vivo experiments?Are there any exposure studies/data for PFI90?In an ideal case studies on primary tumour material would be preferred (in my view) over animal model systems and cell line experiments in order to conclude on clinical/therapeutic utility.
We performed drug tolerability study using P3FI-90 at doses 10 mg/kg, 25 mg/kg, and 50 mg/kg.We found that there was significant weight loss and death at the 50 mg/kg dose while 10 mg/kg and 25 mg/kg were well tolerated without weight loss.Hence, for the first in vivo mouse model study, we started treatment at 20 mg/kg but later, dose was increased to 25 mg/kg which was well tolerated without weight loss.
As for clinically relevant models, we would like to emphasize that P3FI-90 is a tool compound which requires additional Structure Activity Relationships (SAR) studies to make it into a clinical grade drug.We do not claim that P3FI-90 itself will have clinical utility yet and therefore have not added additional PDX models.We have edited the discussion to indicate that additional SAR will be necessary for future clinical utility on page 30 lines 574-577.
* METHOD section: in general, several of the various Materials and Methods chapters (p 29 ff, submitted manuscript) require serious copy editing in order to improve readability and reproducibility.Much of the biochemical protein work (include structural analysis, docking, KDM assay) is insufficiently or not at all described.Much of the biochemical and medchem KDM foundation was laid by the Structural Genomic Consortium and its academic and private partners (for example construct design, cloning, biochemical and structural characterisation, tool compounds; resources that have been shared with Addgene but also Eurofins) and has not been adequately recognized in this manuscript-for example I would expect mention of the PDB codes used for structural modelling, or mention of the PIs in the cloning and construct design (as stipulated by Addgene on their website how to use/cite the resources).The in vitro assay conditions (largely outsourced to Eurofins) need to be stated.Similarly, the peptide substrate sequence for their in vitro KDM assays needs to be detailed (I could not immediately find it in their submitted manuscript).I could not find in the M&M section how they produce/express affinity tagged constructs for their SPR experiments.There is no mention how the authors performed the docking experiments of their identified compounds.
We apologize for these major omissions and thank the reviewer for pointing this out.We have now added more details to the methods section as well as additional references as you have pointed out.Again, we would like to clarify that X-ray crystallography was not part of the manuscript and we apologize for the confusion.We have now completed extensive docking experiments and PDB codes of all structures used have been added.As for the details of the methods from Eurofins experiment, we have added their methods to the supplementary methods section including the peptide substrate information.Lastly, additional details to the KDM3B protein synthesis, expression, and purification have been added to the methods.We thank the reviewers for his/her suggestions with which these modifications have improved our manuscript.Fig. 5A shows almost no change of ChromHMM states in PAX3-FOXO1 sites.In other words, would inhibition of KDM3B by PFI-90 suppress cell growth by reducing transcription in general?They compared PFI-90 vs. DMSO on PAX3-FOXO1 binding sites.If they compare PAX3-FOXO1 binding sites vs. non-binding sites in PFI-90 treated cells, is there any difference between histone modifications?
The reviewer is likely correct.There is a general increase in read counts for H3K9me2 throughout the genome and it may very well downregulate transcription in general.When we compared H3K9me2 reads at PAX3-FOXO1 sites compared to housekeeping genes (non-PAX3-FOXO1 sites), we found that P3FI-90 treatment resulted in 1.9 fold increase over DMSO at PAX3-FOXO1 sites compared to 1.7 fold increase at House Keeping genes (statistically not significant), indicating that H3K9me2 increase is likely general (Rebuttal Fig 7).Since FP-RMS is transcriptionally addicted to PAX3-FOXO1 driven transcription, we believe H3K9me2 increase has a larger impact to PAX3-FOXO1 targets.As for why PAX3-FOXO1 binding is not affected by the increase in H3K9me2, this is likely due to the pioneering effect of PAX3-FOXO1 recently described by the Stanton lab (Sunkel BD, et al 2021 iScience, 24(8); 102867).Rebuttal Figure 7. H3K9me2 ChIP-seq analysis using plotHeatmap at PAX3-FOXO1 sites vs House Keeping genes.Fold increase when comparing P3FI-90 (1uM) treatment vs DMSO for 24 hours.4. Fig. 5C shows that the top 10% of enhancers with the most H3K9me2 increase overlaps significantly with PAX3-FOXO1 sites.It'd be helpful to report the total binding sites of all the TFs listed in the figure.Two scenarios should be distinguished: one is that the H3K9me2 specifically increases in PAX3-FOXO1 sites and another is PAX3-FOXO1 has many more binding sites than the other TFs and it is thus natural to have more overlap with the affected enhancers.
As stated above, we have now performed replicate ChIP-seq for H3K9me2 and performed differential peak analysis as triplicates using diffBind (Ross-Innes, C. et al. 2012 Nature 481, 389-393).This produced 621 upregulated differential peaks and 0 downregulated differential peaks.We determined the nearest genes based on the 621 upregulated peaks and removed duplicate genes resulting in 245 unique genes that showed that PAX3-FOXO1 was the top enriched ChIP-seq profile.
As for the number of genes for each TF in ChEA, we found that the range was between 17 genes to 4931 as below with a mean of 1273 genes (Rebuttal Fig. 9).6.As the histone modifications interplay with each other, KDM3B inhibition may have broad impact on histone modifications.For the ChIP-seq of histone marks, it'd be helpful to identify differentially modified regions between PFI-90 and DMSO.Then check whether the PAX3-FOXO1 sites and target genes are associated with these differentially modified regions.
To determine differentially modified peaks, we performed replicate ChIP-seq for H3K4me3 and H3K9me2.Then we performed differential peak analysis of the triplicate data using diffBind (Ross-Innes, C. et al. 2012 Nature 481, 389-393).As described in point #4, differential peaks for H3K9me2 were all increased after P3FI-90 treatment with no decreased peaks.ChEA analysis on the differential genes identified PAX3-FOXO1 ChIP as the top hit indicating that increase in H3K9me2 peaks were associated with PAX3-FOXO1 sites (Figure 5C).
7. The authors conducted Hi-C experiments to investigate whether chromatin structure is affected by PFI-90 treatment, which is important for understanding how PFI-90 inhibition of KDMs suppresses cell growth.Some additional quantification is needed for the analysis.
First, the similarity of the Hi-C maps between PFI-90 and DMSO should be quantified using such as HiCRep.This will provide a refence to call difference between the two Hi-C experiments.
We performed HiCRep and did not find significant differences between P3FI-90 and DMSO.We have added this to the manuscript (page 25 line 481-482).
Second, there are many methods to detect the differences between Hi-C contact maps such as CHESS (Galan, Nat. Genet., 2020), Zebra (Vian, Cell, 2018), which will give more systematic assessment of the chromatin structure difference.
We also performed CHESS and Zebra analysis and they also did not show significant differences.We have added this to the manuscript (page 25 line 481-482).
Third, the chromatin structure difference may become easier to detect while guided by the differentially modified histone marks.Loop, TAD and compartment comparison can be focused on the regions with differentially modified H3K27ac, H3K9me2, H3K9me3 and H3K4me3.
We performed this analysis and found that differential histone marks for H3K9me2 and H3K4me3 did not significantly overlap directly with Loops and TADs.We believe this highlights the fact that overall, the effect on the Loops and TADs were mild as we have already discussed in the manuscript.There were very small changes to the number of loops but the loops did have a lower APA score indicating that the strength of loops decreased.

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H3K4me3 upregulated differential peak sites Fourth, histone modification changes may alter the modularity of the chromatin structure as shown in a recent study (Zheng and Wang, Nat Commons, 2022).It'd be interesting to compare chromatin modularity changes between PFI-90 and DMSO and check how it affects PAX3-FOXO1 target genes and binding sites.
Modularity of the chromatin from Zheng 2022 Nat Commons paper is determined mostly by H3K27ac histone mark.Our analysis of the cRAM showed that although there was a difference in cRAMs boundaries between PFI90 vs DMSO ( Reviewer #3, expertise in rhabdomyosarcoma epigenomics and models, RNAseq, ChIP-seq, high throughput screening and drug discovery (Remarks to the Author): In their manuscript titled "KDM3B inhibitors disrupt PAX3-FOXO1 oncogenic activity in fusion positive rhabdomyosarcoma," Kim et al. describe a high throughput screen (HTS) using an ARMS cell line engineered to report PAX3-FOXO1 transcriptional activity.As a control, they use a CMV driven reporter line.They identified 64 hits that had specific activity in dose response (DR) and performed in-depth analysis of PFI-63.The molecule altered myogenic differentiation program expression and apoptosis.Timecourse studies were carried out.Another molecule (PFI-90) was identified that had better physical/chemical properties.Within the error for such assays (typically 5-10 fold) these two compounds were equivalent in terms of cellular EC50.The authors went on to show that the molecules inhibited KDM family members with highest potency for KDM3B.However, the IC50 for the enzymes including KDM3B was similar or higher than that for the cells.Binding was analyzed by NMR and SPR and all assays showed similar binding constants (5-10 uM).They went on to perform epigenetic and chromatin profiling and perform dependency screening for KDM3B.They noted that KDM3B was not a dependency in the PedDep portal.They performed limited in vivo testing.Overall, the team set out to identify a PAX3-FOXO1 transcriptional inhibitor and found a small molecule that has modest activity on cells (low micromolar) that they argue inhibits KDM3B.The major concern is the poor binding constant for KDM3B protein and ruling out non-specific effects of the drug on cellular state and survival.
Please note that PFI-63 and PFI-90 has been changed to P3FI-63 and P3FI-90 as per Reviewer #1 recommendation.

Concerns:
1) The EC50 is between 1-10 uM for both compounds and the curve is very steep which raises concerns about specificity of targeting.The authors performed a comprehensive series of studies to try to demonstrate specificity such as NMR and target gene knockdown.
We agree that the curves are steep for some of our cell lines, however as shown in the testing of the NCI60 cell lines, this is not the case for all cell lines, arguing against non-specific toxicity.We also show specificity using enzymatic assays and NMR analysis.We acknowledge that this is a tool compound requiring additional Structure Activity Relationships (SAR) studies to make it into a clinical grade drug.
2) The enzyme inhibition assays for the KDM family members are in vitro assays and show weak inhibitor activity.This is a major concern.How can the cellular EC50 be similar or lower than the enzyme IC50 activity?I suspect the authors will argue that it inhibits multiple family members and this explains the difference.The concern is that this is a non-specific effect on the cells and that would be consistent with the lack of ARMS selectivity.To address this concern, the authors can: a. Demonstrate direct binding of the protein inside cells.
Although these experiments would add to the evidence of binding between P3FI-90 and KDM3B, the experiments are technically difficult to execute.However, the data of In Silico Docking, SPR, and NMR are compelling to show specific binding of P3FI-90 to KDM3B.In addition, the biological result of increased methylation of histones further validate that P3FI-90 does target KDM3B and KDM1A specifically.
b. Compare their compound to other KDM inhibitors mentioned in the discussion.
Thank you for your suggestion.We performed bulk RNA-seq using JIB-04, GSK-J4, and GSK-690.We found that the multi-KDM inhibitors JIB-04 and GSK-J4 both downregulated PAX3-FOXO1 gene sets robustly.This result is consistent with our findings that KDM inhibition by P3FI-63 and P3FI-90 can downregulate PAX3-FOXO1.The KDM1A inhibitor GSK-690 was not able to downregulate PAX3-FOXO1 robustly with only 1 downregulated gene set related to PAX3-FOXO1.However, GSK-690 was able to upregulate apoptosis gene set.These findings are consistent with our data from CRISPRi knockdown of KDM1A which also showed downregulation of PAX3-FOXO1 albeit not as significantly as KDM3B and upregulated apoptosis gene sets.The new results have been added to Supplementary Table 1 Tab 4-6 and results presented on page 8 lines 169-174.
c. Obtain a crystal structure of the compound bound to protein pocket.
We have performed numerous experiments attempting to create crystals with KDM3B and P3FI-63 or P3FI-90 without success.P3FI-63 was too insoluble and not amenable for crystals.P3FI-90 had better solubility but also did not form crystals.We were able to obtain crystals using NOG as the binding partner as published.But when attempts were made to soak the crystal with P3FI-90 to replace NOG, the crystal fell apart.We have also attempted to obtain structural information using CryoEM.Only the structured enzymatic pocket was able to be visualized, and the disordered portion of KDM3B was too difficult to stabilize for CryoEM.We have now performed In Silico Docking experiments which predict binding of P3FI-90 to KDM3B, KDM1A, KDM4B, KDM5A, KDM5B, KDM6A, KDM6B.We found that KDM3B has favorable binding score by Radial Convolutional Neural Net (RTCNN) score.Also, P3FI-90 had the most extensive hydrogen bond interaction with KDM3B.We also found that P3FI-90 had favorable binding score for KDM1A.We have included these results in Fig. 2E, Supplementary Figure 7, Supplementary Table S1 Tab8 and the results presented on page 9 lines 209-255.Thank you for this suggestion and we believe the addition of the in silico docking experiment strengthens our study.d.Make an inactive isomer to distinguish between non-specific chemical properties and selective targeting.
We have shown that P3FI-90 is a multi KDM inhibitor with highest activity against KDM3B, and have demonstrated specificity by enzymatic assays, NMR, and changes in histone modification.We believe manufacturing an inactive isomer is outside the scope of this study.
e. Test other epigenetic drugs in their reporter assay.How do their inhibitors compare to the clinically relevant epigenetic drugs?
In our previous paper (Gryder BE, et al. 2019 Nat Commun 10, 3004), we explored this question using groups of well characterized epigenetic drugs (Rebuttal Fig 11 below).In that publication, we focused on bromodomain inhibitors and HDAC inhibitors given a strong signal in downregulating PAX3-FOXO1 driven ALK-luciferase by multiple drugs in the same class.The signal from KDMs was weaker and only a few KDMis were tested in this study.In our current submission, we started with a novel compound of unknown mechanism of action and identified its targets to be KDM3B and KDM1A.Of note, even for HDACi and BRDi, majority of compounds were only effective at single digit µM or higher which is comparable to P3FI-63 and P3FI-90, indicating KDM inhibition as an effective target for FP-RMS.We appreciated insight of this reviewer, and we believe the suggestions have helped us to improve the manuscript.3) The drug does not appear to be selective for ARMS.A head to head comparison between ARMS and ERMS using O-PDXs may be beneficial.

Rebuttal
Thank you for your assessment.We have provided data in Supplemental Figure 1D that sensitivity for ERMS was in the single digit µM range similar to that of ARMS.We have included in the discussion that increase in H3K9me2 by inhibition of KDM3B is not specifically targeting PAX3-FOXO1 targets but that more likely, it is a general transcriptional downregulation which disproportionately affects PAX3-FOXO1 targets.We agree with the reviewers that this drug is not a selective inhibitor for ARMS and may have cytostatic/cytotoxic activities in other cancer types since arguably all cancers have lineage-specific transcriptional dependencies for survival.Despite showing activity in multiple cell types, the predominant effect on ARMS cells is inhibiting the essential PAX3-FOXO1 coregulatory networks that are unique to this cancer.Further studies will be needed to determine if master transcription factor networks are similarly disrupted in other cancer types.
HiC data did not show global changes to the A and B compartments after P3FI-90 treatment.Given that the nearest genes associated with increased H3K9me2 marks were associated with PAX3-FOXO1 ChIP by CHEA analysis in figure 5C, repression of PAX3-FOXO1 target genes by increased H3K9me2 marks may likely act as a dial to tune the PAX3-FOXO1 sites to a more heterochromatin like state without changing compartments.Description of these results can be found on page 24 lines 453-463.Rebuttal Figure 3. plotCorrelation from the deepTools package using ChIP-seq results from DMSO treated RH4 cells for the following targets: H3K4me3, H3K27ac, H3K9me2, HP1, and KDM3B.Rebuttal Figure 4. ChIP-seq plotHeatmap profile of KDM3B and HP1 at Transcription Start Site(TSS) and PAX3-FOXO1 sites (P3F) after treatment with P3FI-90 vs DMSO for 24 hours.
3. A technical question onFig.5A, why there is almost no signal for H3K9me2 in DMSO even in the heterochromatin state?We apologize for the confusion.The figure is normalized by Gb of state.For example, since 30% of the RH4 chromatin is heterochromatin and active enhancers are only < 1%, we normalized for each of the histone marks by Gb of heterochromatin state and active enhancer state, etc. Below is how the data looks before normalization and you will see that indeed H3K9me2 is enriched in the polychrome and heterochromatin states as expected (Rebuttal Fig 8).However, this figure does not showcase the fact that after P3FI-90 treatment there is disproportionate increase in H3K9me2 at enhancer regions compared to normalized figure.Rebuttal Figure 8. ChromHMM analysis of histone marks and PAX3-FOXO1.Drosophila spike-in adjusted read counts.No normalization for Gb of states.
For PAX3-FOXO1, there are 918 target genes (Cao L, et al Cancer Res.2010;70(16):6497) making it slightly lower than the average TF.Hence it is unlikely that the enrichment we see for PAX3-FOXO1 is a purely mathematical bias.Biologically however, given that FP-RMS is transcriptionally addicted to PAX3-FOXO1 transcriptional targets, it is likely that any perturbation in transcription will most dramatically affect PAX3-FOXO1 target genes.The number of genes for each ChEA transcription factor has been added to Fig 5C and Supplementary Table S5, Tab2.Rebuttal Figure 9. ChEA transcription factor ChIP gene sets from the Enricher website https://maayanlab.cloud/Enrichr/.Plot of number of genes per each transcription factor.5.While H3K27ac intensity does not increase in PAX3-FOXO1 sites, does its intensity increase in all the enhancers?Also, what is the number of H3K27ac peaks in PFI-90 treated cells compared to DMSO? Thank you for this question which is a good way to validate our ChromHMM data.ChromHMM analysis of our ChIP-seq data showed that there is no change in H3K27ac when comparing P3FI-90 treatment vs DMSO.Also, in looking specifically at different enhancer regions, there was also no change in H3K27ac by ChromHMM (Fig. 5A).To validate our ChromHMM results as suggested by this reviewer, we examined if the profile of H3K27ac at all enhancers were different between P3FI-90 vs DMSO.We found that there was no difference in H3K27ac at enhancer sites, consistent with the ChromHMM data (Rebuttal Fig 10).Rebuttal Figure 10.H3K27ac ChIP-seq analysis using plotHeatmap at all enhancer locations.Comparison between DMSO treated H3K27ac ChIP-seq vs P3FI-90 treated (1uM, 24 hours).As for the number of H3K27ac peaks, we used MACS2 to call peaks and using a pvalue cutoff of 1x10 -7 , there were 49,398 peaks in P3FI-90 treated cells and 48,180 peaks for DMSO, indicating again no significant change in H3K27ac after P3FI-90 treatment.We have now modified the manuscript to describe these results on page 22 line 423-425 and Supplementary Fig 11A.
Figure 11.Result of drug screen using RH4 cell lines modified with ALK super enhancer PAX3-FOXO1 binding driven Luciferase, CMV driven Luciferase, and XTT assay.Drugs categorized by type of response: PAX3-FOXO1 Super Enhancer selective, ALK-Luc down CMV-Luc up (or HDAC-like) response, or non-specific.
Table of TAD and Loop analysis delineated by H3K4me3 differential peaks and H3K9me2 differential peaks.Total number of TADs and Loops identified by HiC was used to determine how many of the TADs and Loops overlapped with H3K4me3 and H3K9me2 differential peaks.